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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗

Purple is the new green: biopigments and spectra of Earth-like purple worlds

ABSTRACT With more than 5500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also colour their habitats and could dominate a much wider range of environments on Earth-like exoplanets. Here, we characterize the reflectance spectra of a collection of purple sulfur and purple non-sulfur bacteria from a variety of anoxic and oxic environments. We present models for Earth-like planets where purple bacteria dominate the surface and show the impact of their signatures on the reflectance spectra of terrestrial exoplanets. Our research provides a new resource to guide the detection of purple bacteria and improves our chances of detecting life on exoplanets with upcoming telescopes. Our biological pigment data base for purple bacteria and the high-resolution spectra of Earth-like planets, including ocean worlds, snowball planets, frozen worlds, and Earth analogues, are available online, providing a tool for modellers and observers to train retrieval algorithms, optimize search strategies, and inform models of Earth-like planets, where purple is the new green.

Coelho, Lígia Fonseca (ORCID:0000000150081249)↗

Peak microhardness recovery via T6 heat treatment with extremely soft annealed Al7075 feedstock in additive friction stir deposition

With standard T6 heat treatments, precipitate-hardened alloys such as Al7075 and Al6061 fabricated using Additive Friction Stir Deposition (AFSD) method restore to noticeablely different peak mechanical properties. Previous research observed similar results but did not provide a viable solution. This study proposes a new processing strategy, namely enhanced plastic deformation by subjecting the Al7075 feedstock to annealed softening treatments. Specifically, by annealing the standard T651-Al7075 feedstock and deposition substrate (179 HV), their Microhardness were first degraded to its lowest state (80 HV), which is called a Soft-to-Soft system. For the Soft-to-Soft system subjected to AFSD, after undergoing appropriate T6 heat treatment, the microhardness of the AFSD 7075 alloy was restored to its peak value (183.1 ± 1.8 HV). The results indicate that this softening strategy can effectively reduce the non-strengthening phase in the AFSD matrix, thereby increasing the strengthening phase (η′ phase). This addresses the issue of traditional AFSD-prepared aluminum alloys being unable to achieve peak performance through T6 heat treatment.

36 MATERIALS SCIENCE↗

Mechanistic Differences between Electrochemical Hydrogenation and Hydrogenolysis of 5‐Hydroxymethylfurfural and Their pH Dependence

Abstract Hydrogenation and hydrogenolysis are two important reactions for electrochemical reductive valorization of biomass‐derived oxygenates such as 5‐hydroxymethylfurfural (HMF). In general, hydrogenolysis (which combines hydrogenation and deoxygenation) is more challenging than hydrogenation (which does not involve the cleavage of carbon–oxygen bonds). Thus, identifying factors and conditions that can promote hydrogenolysis is of great interest for reductive valorization of biomass‐derived oxygenates. For the electrochemical reduction of HMF and its derivatives, it is known that aldehyde hydrogenation is not a part of aldehyde hydrogenolysis but rather a competing reaction; however, no atomic‐level understanding is currently available to explain their electrochemical mechanistic differences. In this study, combined experimental and computational investigations were performed using Cu electrodes to elucidate the key mechanistic differences between electrochemical hydrogenation and hydrogenolysis of HMF. The results revealed that hydrogenation and hydrogenolysis of HMF involve the formation of different surface‐adsorbed intermediates via different reduction mechanisms and that lowering the pH promoted the formation of the intermediates required for aldehyde and alcohol hydrogenolysis. This study for the first time explains the origins of the experimentally observed pH‐dependent selectivities for hydrogenation and hydrogenolysis and offers a new mechanistic foundation upon which rational strategies to control electrochemical hydrogenation and hydrogenolysis can be developed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stable, high-performance, dendrite-free, seawater-based aqueous batteries

Metal anode instability, including dendrite growth, metal corrosion, and hetero-ions interference, occurring at the electrolyte/electrode interface of aqueous batteries, are among the most critical issues hindering their widespread use in energy storage. Herein, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals). An in-situ optical visualization coupled with finite element analysis is utilized to mimic actual electrochemical environments analogous to the actual aqueous batteries and analyze the complex electrochemical behaviors. The Zn-Mn alloy anodes achieved stability over thousands of cycles even under harsh electrochemical conditions, including testing in seawater-based aqueous electrolytes and using a high current density of 80 mA cm –2 . The proposed design strategy and the in-situ visualization protocol for the observation of dendrite growth set up a new milestone in developing durable electrodes for aqueous batteries and beyond.

25 ENERGY STORAGE↗

Inferring Neutron Star Merger Ejecta Morphology with Kilonovae

In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.

79 ASTRONOMY AND ASTROPHYSICS↗

Designing an Optimal Kilonova Search Using DECam for Gravitational-wave Events

We address the problem of optimally identifying all kilonovae detected via gravitational-wave emission in the upcoming LIGO/Virgo/KAGRA observing run, O4, which is expected to be sensitive to a factor of ~7 more binary neutron star (BNS) alerts than previously. Electromagnetic follow-up of all but the brightest of these new events will require >1 m telescopes, for which limited time is available. We present an optimized observing strategy for the DECam during O4. We base our study on simulations of gravitational-wave events expected for O4 and wide-prior kilonova simulations. We derive the detectabilities of events for realistic observing conditions. We optimize our strategy for confirming a kilonova while minimizing telescope time. For a wide range of kilonova parameters, corresponding to a fainter kilonova compared to GW170817/AT 2017gfo, we find that, with this optimal strategy, the discovery probability for electromagnetic counterparts with the DECam is ~80% at the nominal BNS gravitational-wave detection limit for O4 (190 Mpc), which corresponds to an ~30% improvement compared to the strategy adopted during the previous observing run. For more distant events (~330 Mpc), we reach an ~60% probability of detection, a factor of ~2 increase. For a brighter kilonova model dominated by the blue component that reproduces the observations of GW170817/AT 2017gfo, we find that we can reach ~90% probability of detection out to 330 Mpc, representing an increase of ~20%, while also reducing the total telescope time required to follow up events by ~20%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Impact of fused silica debris shields and enhanced mitigation techniques on large-aperture beam-sampling optics for the National Ignition Facility

Here, we show that the large-scale routine use of the fused silica debris shield (FSDS) maintains the ∼100× reduction in damage initiation rate and 70% increase in the install lifetime of a new grating debris shield (GDS) observed during pilot operations. Furthermore, we show that the install lifetimes of recycled GDS optics are nearly tripled using additional mitigation strategies such as expanding mitigation processing to include all damage sites larger than 10 μm (LT10) rather than just larger than 50 μm (LT50) and FSDS. We note that there is still a 50% difference between new and recycled optic installation lifetimes. We show that recycled optics have a 3.5× higher apparent initiation rate than new optics when exposed to nominally identical laser conditions.

FSDS↗

A new method for obtaining model-free viscoelastic material properties from atomic force microscopy experiments using discrete integral transform techniques

Viscoelastic characterization of materials at the micro- and the nanoscale is commonly performed with the aid of force–distance relationships acquired using atomic force microscopy (AFM). The general strategy for existing methods is to fit the observed material behavior to specific viscoelastic models, such as generalized viscoelastic models or power-law rheology models, among others. Here we propose a new method to invert and obtain the viscoelastic properties of a material through the use of the Z-transform, without using a model. We present the rheological viscoelastic relations in their classical derivation and their z-domain correspondence. We illustrate the proposed technique on a model experiment involving a traditional ramp-shaped force–distance AFM curve, demonstrating good agreement between the viscoelastic characteristics extracted from the simulated experiment and the theoretical expectations. We also provide a path for calculating standard viscoelastic responses from the extracted material characteristics. The new technique based on the Z-transform is complementary to previous model-based viscoelastic analyses and can be advantageous with respect to Fourier techniques due to its generality. Additionally, it can handle the unbounded inputs traditionally used to acquire force–distance relationships in AFM, such as ramp functions, in which the cantilever position is displaced linearly with time for a finite period of time.

36 MATERIALS SCIENCE↗

New frontiers in wind-wildlife monitoring systems

Effective minimization of negative effects of wind energy on wildlife is an iterative process whereby direct observations of wildlife effects inform and validate mitigation strategies. Yet, the full implementation of this adaptive management has been hindered by a lack of appropriate data. The accurate, high-resolution data required exceeds the capacity of most current monitoring approaches (human observers or monitoring technologies applied in isolation). Current applications of monitoring technologies struggle to harness their full potential by failing to capitalize on opportunities for integration with additional technologies and/or by having limited temporal and spatial resolution. At the emergence of this new frontier of wildlife monitoring, we review the elements of a robust wind-wildlife monitoring system and highlight sensor fusion principles that facilitate effective implementation and integration of multiple monitoring technologies. We also illustrate how sensor fusion solutions can generate high resolution data on collision and displacement effects on terrestrial wildlife across complex spatial and temporal scales.

17 WIND ENERGY↗

Incorporating uncertainty for enhanced leaderboard scoring and ranking in data competitions

Data competitions have become a popular and cost-effective approach for crowdsourcing versatile solutions from diverse expertise. Current practice relies on the simple leaderboard scoring based on a given set of competition data for ranking competitors and distributing the prize. However, a disadvantage of this practice in many competitions is that a slight difference in the scores due to the natural variability of the observed data could result in a much larger difference in the prize amounts. In this article, we propose a new strategy to quantify the uncertainty in the rankings and scores from using different data sets that share common characteristics with the provided competition data. By using a bootstrap approach to generate many comparable data sets, the new method has four advantages over current practice. Furthermore, during the competition, it provides a mechanism for competitors to get feedback about the uncertainty in their relative ranking. After the competition, it allows the host to gain a deeper understanding of the algorithm performance and their robustness across representative data sets. It also offers a transparent mechanism for prize distribution to reward the competitors more fairly with superior and robust performance. Finally, it has the additional advantage of being able to explore what results might have looked like if competition goals evolved from their original choices. The implementation of the strategy is illustrated with a real data competition hosted by Topcoder on urban radiation search.

42 ENGINEERING↗

Unveiling the Arsenal of Apple Bitter Rot Fungi: Comparative Genomics Identifies Candidate Effectors, CAZymes, and Biosynthetic Gene Clusters in Colletotrichum Species

The bitter rot of apple is caused by Colletotrichum spp. and is a serious pre-harvest disease that can manifest in postharvest losses on harvested fruit. In this study, we obtained genome sequences from four different species, C. chrysophilum, C. noveboracense, C. nupharicola, and C. fioriniae, that infect apple and cause diseases on other fruits, vegetables, and flowers. Our genomic data were obtained from isolates/species that have not yet been sequenced and represent geographic-specific regions. Genome sequencing allowed for the construction of phylogenetic trees, which corroborated the overall concordance observed in prior MLST studies. Bioinformatic pipelines were used to discover CAZyme, effector, and secondary metabolic (SM) gene clusters in all nine Colletotrichum isolates. We found redundancy and a high level of similarity across species regarding CAZyme classes and predicted cytoplastic and apoplastic effectors. SM gene clusters displayed the most diversity in type and the most common cluster was one that encodes genes involved in the production of alternapyrone. Our study provides a solid platform to identify targets for functional studies that underpin pathogenicity, virulence, and/or quiescence that can be targeted for the development of new control strategies. With these new genomics resources, exploration via omics-based technologies using these isolates will help ascertain the biological underpinnings of their widespread success and observed geographic dominance in specific areas throughout the country.

59 BASIC BIOLOGICAL SCIENCES↗

Supported Pt Nanoparticles on Mesoporous Titania for Selective Hydrogenation of Phenylacetylene

Semi-hydrogenation of alkynes to alkenes is one of the most important industrial reactions. However, it remains technically challenging to obtain high alkene selectivity especially at a high alkyne conversion because of kinetically favorable over hydrogenation. In this contribution, we show that supported ultrasmall Pt nanoparticles (2.5 nm) on mesoporous TiO2 (Pt@mTiO2) remarkably improve catalytic performance toward semi-hydrogenation of phenylacetylene. Pt@mTiO2 is prepared by co-assembly of Pt and Ti precursors with silica colloidal templates via an evaporation-induced self-assembly process, followed by further calcination for thermal decomposition of Pt precursors and crystallization of mTiO2 simultaneously. As-resultant Pt@mTiO2 discloses a high hydrogenation activity of phenylacetylene, which is 2.5 times higher than that of commercial Pt/C. More interestingly, styrene selectivity over Pt@mTiO2 remains 100% in a wide phenylacetylene conversion window (20–75%). The styrene selectivity is >80% even at 100% phenylacetylene conversion while that of the commercial Pt/C is 0%. The remarkable styrene selectivity of the Pt@mTiO2 is derived from the weakened styrene adsorption strength on the atop Pt sites as observed by diffuse reflectance infrared Fourier transform spectroscopy with CO as a probe molecule (CO-DRIFTS). Our strategy provides a new avenue for promoting alkyne to alkene transformation in the kinetically unfavorable region through novel catalyst preparation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mobility Data and Models Informing Smart Cities

This presentation explores the interactions of Emerging Technology, Changing Urban Environments, and Urban Travel Behavior on Mobility and Energy Impacts. Key findings include quantifying impacts of emerging mobility, access and infrastructure associated with new mobility choices and services in urban areas. The results demonstrate new data collection methods and capabilities to understand and identify key levers to improve energy productivity of future mobility systems and of quickly evolving MaaS and COVID-19 contexts to monitor rapidly shifting urban mobility patterns. Under development are mode choice models for new modes versus traditional modes. Initial estimates are developed on the potential of workforce mobility strategies in shaping future energy-efficient mobility system impacts. For mode replacement and workforce mobility, this presentation offers observability into the changes in number of transactions per mode, after ride-hailing/TNC/MaaS introduction and in origins of workforce to enable user need-driven reimagining of efficient mobility systems: Seattle (SEA-TAC) airport: for every 100 new TNC transactions for ground transportation, ~27% replaced transit, 35% replaced parking, 17% replaced car rentals, and 21% replaced taxis. Similarly, at Denver International (DEN), ride-hailing transactions replaced transit, parking, car rental and taxis at a rate of 34.7%, 39.0%, 16.6%, and 9.7%, respectively. A workforce mobility tool, analysis/visualization techniques, and capabilities to understand and identify key job commute needs, new choices in access to job opportunities, and affordability aspects as levers to improve energy productivity of future integrated urban mobility systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Spectroscopic signature of negative electronic compressibility from the Ti core-level of titanium carbonitride MXene

Two-dimensional transition metal carbides, carbonitrides, and nitrides called MXenes exhibit high metallic conductivity, ion intercalation capability and reversible redox activity, prompting their applications in energy storage and conversion, electromagnetic interference (EMI) shielding, and electronics, among many other fields. It has been shown that replacement of about 50% of carbon atoms in the most popular MXene family member, titanium carbide (Ti 3 C 2 T x ), by nitrogen atoms, forming titanium carbonitride (Ti 3 CNT x ), leads to drastically different properties, such as very high negative charge in solution and extreme EMI shielding effectiveness, exceeding all known materials, even metals at comparable thicknesses. Here, by using ultraviolet photoemission spectroscopy (UPS), the electronic structures of Ti 3 CNT x and Ti 3 C 2 T x are systematically investigated and compared as a function of charge carrier density. We observe that, in contrast to Ti 3 C 2 T x , the Ti 3p core-level of Ti 3 CNT x exhibits a counterintuitive shift to a lower binding energy of up to approximately 250 meV upon increasing the electron density, which is a spectroscopic signature of negative electronic compressibility (NEC). These experimentally measured chemical potential shifts are well-captured by the density functional theory (DFT) calculation. The DFT results also further suggest that the hybridization of titanium-nitrogen bonding in Ti 3 CNT x helps promoting the available states of Ti atoms for receiving more electron above the Fermi level and leads to the observed NEC. Furthermore, our findings explain the differences in electronic properties between the two very important and widely studied MXenes and also suggest a new strategy to apply the NEC effect of Ti 3 CNT x in energy and charge storage applications.

2D materials↗

Streaming Generalized Canonical Polyadic Tensor Decompositions

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allows for arbitrary objective functions which the CP model attempts to minimize. This approach can provide better fits and more interpretable models when the observed tensor data is strongly non-Gaussian. In the streaming case, tensor data is gradually observed over time and the algorithm must incrementally update a GCP factorization with limited access to prior data. In this work, we extend the GCP formalism to the streaming context by deriving a GCP optimization problem to be solved as new tensor data is observed, formulate a tunable history term to balance reconstruction of recently observed data with data observed in the past, develop a scalable solution strategy based on segregated solves using stochastic gradient descent methods, describe a software implementation that provides performance and portability to contemporary CPU and GPU architectures and integrates with Matlab for enhanced usability, and demonstrate the utility and performance of the approach and software on several synthetic and real tensor data sets.

97 MATHEMATICS AND COMPUTING↗

Kinematic Variables and Feature Engineering for Particle Phenomenology

Kinematic variables have been playing an important role in collider phenomenology, as they expedite discoveries of new particles by separating signal events from unwanted background events and allow for measurements of particle properties such as masses, couplings, spins, etc. For the past 10 years, an enormous number of kinematic variables have been designed and proposed, primarily for the experiments at the Large Hadron Collider, allowing for a drastic reduction of high-dimensional experimental data to lower-dimensional observables, from which one can readily extract underlying features of phase space and develop better-optimized data-analysis strategies. We review these recent developments in the area of phase space kinematics, summarizing the new kinematic variables with important phenomenological implications and physics applications. We also review recently proposed analysis methods and techniques specifically designed to leverage the new kinematic variables. As machine learning is nowadays percolating through many fields of particle physics including collider phenomenology, we discuss the interconnection and mutual complementarity of kinematic variables and machine learning techniques. We finally discuss how the utilization of kinematic variables originally developed for colliders can be extended to other high-energy physics experiments including neutrino experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗